Along with information and communication technique development, an era of big data has come. Data amount needed to store in every industry has become bigger and bigger, especially for the industry in need of storing huge user data, such as finance, telecom, network communication service (email, instant messaging), social networking service (microblog, forum), etc.
Generally, the big data are distributedly stored in a number of servers. Number of the server that stores the big data may be thousands or ten thousand. These servers may be located in one or more server groups, or in one or more data processing centers. A data storage way of some databases is a distributed storage way too, such as xcube database. Xcube is a distributed NoSQL database, and it divides a data table with big data amount into a number of sub tables, stores the sub tables into a number of servers and records sub table information into a routing table. The sub table information includes a start line key value, an end line key value, data amount of the sub table and a server where the sub table is located. The start line key value and the end line key value of the sub table mean respective values of main keys of a start line and an end line of the sub table. The sub table includes all records between a location in a father data table corresponding to the start line key value and a location in the father data table corresponding to the end line key value.
Fast processing of the big data is a problem that people face. Processing way of multithreading and multitask can concurrently process data that a single device stores. However, how to coordinate servers in the server group to concurrently process distributed big data and increase processing speed of big data is a problem to be solved.